From 240ec5e581d3734376a4f0b4b7c6d007cb9faefb Mon Sep 17 00:00:00 2001
From: "Harle, Antoine (Contracteur)" <Antoine.Harle@Teledyne.com>
Date: Fri, 6 Dec 2019 14:19:05 -0500
Subject: [PATCH] Test MobileNet Brutus

---
 higher/test_brutus.py | 24 +++++++++++++-----------
 higher/test_dataug.py |  1 -
 2 files changed, 13 insertions(+), 12 deletions(-)

diff --git a/higher/test_brutus.py b/higher/test_brutus.py
index 60af723..8a5dd85 100755
--- a/higher/test_brutus.py
+++ b/higher/test_brutus.py
@@ -35,18 +35,21 @@ if __name__ == "__main__":
 
 
     n_inner_iter = 1
-    epochs = 100
+    epochs = 150
     dataug_epoch_start=0
 
+    #model = LeNet(3,10)
+    model = MobileNetV2(num_classes=10)
+    #model = WideResNet(num_classes=10, wrn_size=32)
+
     tf_dict = {k: TF.TF_dict[k] for k in tf_names}
 
     t0 = time.process_time()
 
-    aug_model = Augmented_model(Data_augV5(TF_dict=tf_dict, N_TF=3, mix_dist=0.0, fixed_prob=False, fixed_mag=False, shared_mag=False), WideResNet(num_classes=10, wrn_size=32)).to(device)
-    #aug_model = Augmented_model(RandAug(TF_dict=tf_dict, N_TF=2), WideResNet(num_classes=10, wrn_size=32)).to(device)
-    print(str(aug_model), 'on', device_name)
-    #run_simple_dataug(inner_it=n_inner_iter, epochs=epochs)
-    log= run_dist_dataugV2(model=aug_model, epochs=epochs, inner_it=n_inner_iter, dataug_epoch_start=dataug_epoch_start, print_freq=None, loss_patience=None)
+    aug_model = Augmented_model(Data_augV5(TF_dict=tf_dict, N_TF=3, mix_dist=0.0, fixed_prob=True, fixed_mag=True, shared_mag=True), model).to(device)
+    
+    print("{} on {} for {} epochs - {} inner_it".format(str(aug_model), device_name, epochs, n_inner_iter))
+    log= run_dist_dataugV2(model=aug_model, epochs=epochs, inner_it=n_inner_iter, dataug_epoch_start=dataug_epoch_start, print_freq=10, KLdiv=True, loss_patience=None)
 
     exec_time=time.process_time() - t0
     ####
@@ -60,11 +63,10 @@ if __name__ == "__main__":
     ####
     t0 = time.process_time()
 
-    #aug_model = Augmented_model(Data_augV5(TF_dict=tf_dict, N_TF=3, mix_dist=0.0, fixed_prob=False, fixed_mag=False, shared_mag=False), WideResNet(num_classes=10, wrn_size=32)).to(device)
-    aug_model = Augmented_model(RandAug(TF_dict=tf_dict, N_TF=2), WideResNet(num_classes=10, wrn_size=32)).to(device)
-    print(str(aug_model), 'on', device_name)
-    #run_simple_dataug(inner_it=n_inner_iter, epochs=epochs)
-    log= run_dist_dataugV2(model=aug_model, epochs=epochs, inner_it=n_inner_iter, dataug_epoch_start=dataug_epoch_start, print_freq=None, loss_patience=None)
+    aug_model = Augmented_model(RandAug(TF_dict=tf_dict, N_TF=2), model).to(device)
+
+    print("{} on {} for {} epochs - {} inner_it".format(str(aug_model), device_name, epochs, n_inner_iter))
+    log= run_dist_dataugV2(model=aug_model, epochs=epochs, inner_it=n_inner_iter, dataug_epoch_start=dataug_epoch_start, print_freq=10, KLdiv=True, loss_patience=None)
 
     exec_time=time.process_time() - t0
     ####
diff --git a/higher/test_dataug.py b/higher/test_dataug.py
index ec3dbce..87dae1e 100755
--- a/higher/test_dataug.py
+++ b/higher/test_dataug.py
@@ -149,7 +149,6 @@ if __name__ == "__main__":
         #aug_model = Augmented_model(RandAug(TF_dict=tf_dict, N_TF=2), model).to(device)
 
         print("{} on {} for {} epochs - {} inner_it".format(str(aug_model), device_name, epochs, n_inner_iter))
-        #run_simple_dataug(inner_it=n_inner_iter, epochs=epochs)
         log= run_dist_dataugV2(model=aug_model, epochs=epochs, inner_it=n_inner_iter, dataug_epoch_start=dataug_epoch_start, print_freq=10, KLdiv=True, loss_patience=None)
 
         exec_time=time.process_time() - t0